Image processing method and image processor performing the same

ABSTRACT

In an image processing method that converts image data into output data by performing tone mapping, an edge of an image represented by the image data is determined, a first tone mapping operation is performed on first image data included in the image data, where the first image data represent a first portion of the image not including the edge, whether a gray level of second image data is within a predetermined gray range is determined, where the second image data represent a second portion of the image including the edge, a second tone mapping operation is performed on the second image data when the gray level of the second image data is within the gray range, and the first tone mapping operation is performed on the second image data when the gray level of the second image data is not within the gray range.

This application claims priority to Korean Patent Application No.10-2017-0155735, filed on Nov. 21, 2017 and all the benefits accruingtherefrom under 35 U.S.C. § 119, the content of which in its entirety isherein incorporated by reference.

BACKGROUND 1. Field

Exemplary embodiments of the invention relate to image processingprocessors, and more particularly to image processing methods capable ofimproving accuracy at edge portions and image processors performing theimage processing methods.

2. Description of the Related Art

Generally, when a dynamic range of a display device is different from adynamic range of original image data, the original image data may beconverted corresponding to the dynamic range of the display device.Further, various display devices having different dynamic ranges maydisplay an image corresponding to the original image data by convertingthe original image data corresponding to the dynamic ranges of thevarious display devices. This operation that converts the dynamic rangeof the original image data to match the dynamic range of the displaydevice may be referred to as tone mapping.

SUMMARY

By a tone mapping, image quality at a low gray region and a high grayregion may be lowered, and an edge of an image may not be accuratelydisplayed.

Some exemplary embodiments provide an image processing method capable ofimproving accuracy of an edge portion.

Some exemplary embodiments provide an image processor performing theimage processing method.

According to exemplary embodiments, there is provided an imageprocessing method that converts image data into output data byperforming tone mapping. In the image processing method, an edge of animage represented by the image data is determined, a first tone mappingoperation is performed on first image data included in the image data,where the first image data represent a first portion of the image notincluding the edge, whether a gray level of second image data is withina predetermined gray range is determined, where the second image datarepresent a second portion of the image including the edge, a secondtone mapping operation is performed on the second image data when thegray level of the second image data is within the predetermined grayrange, and the first tone mapping operation is performed on the secondimage data when the gray level of the second image data is not withinthe predetermined gray range.

In an exemplary embodiment, the first tone mapping operation may convertthe image data into the output data using a first conversion function,and the second tone mapping operation may convert the image data intothe output data using a second conversion function different from thefirst conversion function.

In an exemplary embodiment, the predetermined gray range may include atleast one of a first gray range less than a first threshold gray leveland a second gray range greater than a second threshold gray level, andthe second threshold gray level may be greater than the first thresholdgray level.

In an exemplary embodiment, in the first gray range, the output datagenerated by the first tone mapping operation may be less than or equalto the output data generated by the second tone mapping operation.

In an exemplary embodiment, in the second gray range, the output datagenerated by the first tone mapping operation may be greater than orequal to the output data generated by the second tone mapping operation.

In an exemplary embodiment, at least one of the first gray range and thesecond gray range may be adjusted based on an average gray level of theimage data.

In an exemplary embodiment, a first absolute difference between theimage data and the output data generated by the first tone mappingoperation may be greater than or equal to a second absolute differencebetween the image data and the output data generated by the second tonemapping operation.

In an exemplary embodiment, to determine the edge of the image, a dataformat of the image data may be converted from an RGB format to aconversion image format where luminance data and chrominance data areseparated, and the edge may be determined by applying a high-pass filterto the luminance data.

In an exemplary embodiment, a number of pixels included in the edge maybe obtained, and a bypass operation may be performed on an entirety ofthe image data when the number of pixels is greater than a firstthreshold value.

In an exemplary embodiment, the output data generated by the bypassoperation may increase in linear proportion to an increase of a graylevel of the image data.

In an exemplary embodiment, the second tone mapping operation mayconvert the image data corresponding to a first color into the outputdata by a second conversion function to which a first weight is applied,and may convert the image data corresponding to a second color differentfrom the first color into the output data by the second conversionfunction to which a second weight different from the first weight isapplied.

According to exemplary embodiments, there is provided an imageprocessing method that converts image data into output data byperforming tone mapping. In the image processing method, a number ofpixels included in an edge of an image represented by the image data isobtained, a bypass operation is performed on the image data when thenumber of pixels is greater than a first threshold value, and a firsttone mapping operation is performed on the image data when the number ofpixels is less than or equal to the first threshold value.

In an exemplary embodiment, the output data generated by the bypassoperation may increase in linear proportion to an increase of a graylevel of the image data.

According to example embodiments, there is provided an image processorthat converts image data into output data by performing tone mapping.The image processor includes a signal receiver receiving image contentsincluding the image data and meta data for the image data, a tone mapperdetermining an edge of an image represented by the image data,performing a first tone mapping operation on first image data includedin the image data, where the first image data represent a first portionof the image not including the edge, determining whether a gray level ofsecond image data is within a predetermined gray range, where the secondimage data represent a second portion of the image including the edge,performing a second tone mapping operation on the second image data whenthe gray level of the second image data is within the predetermined grayrange, and performing the first tone mapping operation on the secondimage data when the gray level of the second image data is not withinthe predetermined gray range, and an image controller performing apost-processing operation on the image based on the output data and themeta data.

In an exemplary embodiment, the first tone mapping operation may convertthe image data into the output data using a first conversion function,and the second tone mapping operation may convert the image data intothe output data using a second conversion function different from thefirst conversion function.

In an exemplary embodiment, the predetermined gray range may include atleast one of a first gray range less than a first threshold gray leveland a second gray range greater than a second threshold gray level, andthe second threshold gray level may be greater than the first thresholdgray level.

In an exemplary embodiment, in the first gray range, the output datagenerated by the first tone mapping operation may be less than or equalto the output data generated by the second tone mapping operation.

In an exemplary embodiment, in the second gray range, the output datagenerated by the first tone mapping operation may be greater than orequal to the output data generated by the second tone mapping operation.

In an exemplary embodiment, the tone mapper may obtain a number ofpixels included in the edge, and perform a bypass operation on anentirety of the image data when the number of pixels is greater than afirst threshold value.

In an exemplary embodiment, the second tone mapping operation mayconvert the image data corresponding to a first color into the outputdata by a second conversion function to which a first weight is applied,and may convert the image data corresponding to a second color differentfrom the first color into the output data by the second conversionfunction to which a second weight different from the first weight isapplied.

As described above, the image processing method according to exemplaryembodiments may detect an edge of an image. The image processing methodmay apply relaxed tone mapping (or perform the second tone mappingoperation) to a high gray edge or a low gray edge, or may apply lineartone mapping (or a bypass operation) when the number of pixels includedin an edge of an image is greater than a threshold value. Accordingly,the image processing method may prevent a detail loss of an edge in lowand high gray regions, and may prevent image distortion caused by highdynamic range (“HDR”) image processing.

Further, the image processor according to exemplary embodiments mayperform appropriate tone mapping operations according to characteristicsor conditions (e.g., a gray range, a color, etc. of an edge) of imagedata, thereby preventing the detail loss of the edge and the imagedistortion caused by the HDR image processing.

BRIEF DESCRIPTION OF THE DRAWINGS

Illustrative, non-limiting exemplary embodiments will be more clearlyunderstood from the following detailed description in conjunction withthe accompanying drawings.

FIG. 1 is a block diagram illustrating an exemplary embodiment of animage processor.

FIG. 2 is a flowchart illustrating an exemplary embodiment of an imageprocessing method.

FIGS. 3A through 3C are diagrams for describing an operation thatdetermines a low gray edge or a high gray edge in an image processingmethod of FIG. 2.

FIG. 4A is a graph for describing a first tone mapping operation in animage processing method of FIG. 2.

FIG. 4B is a graph for describing a second tone mapping operation in animage processing method of FIG. 2.

FIG. 5A is a graph for describing output data by a first tone mappingoperation in an image processing method of FIG. 2.

FIG. 5B is a graph for describing output data by a second tone mappingoperation in an image processing method of FIG. 2.

FIG. 6A is a diagram illustrating an example of an image generated by afirst tone mapping operation in an image processing method of FIG. 2.

FIG. 6B is a diagram illustrating an example of an image generated by asecond tone mapping operation in an image processing method of FIG. 2.

FIG. 7 is a flowchart illustrating an exemplary embodiment of an imageprocessing method.

FIG. 8A is a diagram illustrating an example of an image generated by afirst tone mapping operation in an image processing method of FIG. 7.

FIG. 8B is a diagram illustrating an example of an image generated by asecond tone mapping operation in an image processing method of FIG. 7.

FIG. 9 is a flowchart illustrating an exemplary embodiment of an imageprocessing method.

FIG. 10 is a graph for describing an operation that sets differentweights according to colors of image data an image processing method ofFIG. 9.

FIG. 11 is a flowchart illustrating an exemplary embodiment of an imageprocessing method.

DETAILED DESCRIPTION

Hereinafter, embodiments of the invention will be explained in detailwith reference to the accompanying drawings. This invention may,however, be embodied in many different forms, and should not beconstrued as limited to the embodiments set forth herein. Rather, theseembodiments are provided so that this invention will be thorough andcomplete, and will fully convey the scope of the invention to thoseskilled in the art. Like reference numerals refer to like elementsthroughout.

It will be understood that when an element is referred to as being “on”another element, it can be directly on the other element or interveningelements may be therebetween. In contrast, when an element is referredto as being “directly on” another element, there are no interveningelements present.

It will be understood that, although the terms “first,” “second,”“third” etc. may be used herein to describe various elements,components, regions, layers and/or sections, these elements, components,regions, layers and/or sections should not be limited by these terms.These terms are only used to distinguish one element, component, region,layer or section from another element, component, region, layer orsection. Thus, “a first element,” “component,” “region,” “layer” or“section” discussed below could be termed a second element, component,region, layer or section without departing from the teachings herein.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting. As used herein, thesingular forms “a,” “an,” and “the” are intended to include the pluralforms, including “at least one,” unless the content clearly indicatesotherwise. “Or” means “and/or.” As used herein, the term “and/or”includes any and all combinations of one or more of the associatedlisted items. It will be further understood that the terms “comprises”and/or “comprising,” or “includes” and/or “including” when used in thisspecification, specify the presence of stated features, regions,integers, steps, operations, elements, and/or components, but do notpreclude the presence or addition of one or more other features,regions, integers, steps, operations, elements, components, and/orgroups thereof.

Furthermore, relative terms, such as “lower” or “bottom” and “upper” or“top,” may be used herein to describe one element's relationship toanother element as illustrated in the Figures. It will be understoodthat relative terms are intended to encompass different orientations ofthe device in addition to the orientation depicted in the Figures. In anexemplary embodiment, when the device in one of the figures is turnedover, elements described as being on the “lower” side of other elementswould then be oriented on “upper” sides of the other elements. Theexemplary term “lower,” can therefore, encompasses both an orientationof “lower” and “upper,” depending on the particular orientation of thefigure. Similarly, when the device in one of the figures is turned over,elements described as “below” or “beneath” other elements would then beoriented “above” the other elements. The exemplary terms “below” or“beneath” can, therefore, encompass both an orientation of above andbelow.

“About” or “approximately” as used herein is inclusive of the statedvalue and means within an acceptable range of deviation for theparticular value as determined by one of ordinary skill in the art,considering the measurement in question and the error associated withmeasurement of the particular quantity (i.e., the limitations of themeasurement system). For example, “about” can mean within one or morestandard deviations, or within ±30%, 20%, 10%, 5% of the stated value.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this invention belongs. It will befurther understood that terms, such as those defined in commonly useddictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art and theinvention, and will not be interpreted in an idealized or overly formalsense unless expressly so defined herein.

Exemplary embodiments are described herein with reference to crosssection illustrations that are schematic illustrations of idealizedembodiments. As such, variations from the shapes of the illustrations asa result, for example, of manufacturing techniques and/or tolerances,are to be expected. Thus, embodiments described herein should not beconstrued as limited to the particular shapes of regions as illustratedherein but are to include deviations in shapes that result, for example,from manufacturing. In an exemplary embodiment, a region illustrated ordescribed as flat may, typically, have rough and/or nonlinear features.Moreover, sharp angles that are illustrated may be rounded. Thus, theregions illustrated in the figures are schematic in nature and theirshapes are not intended to illustrate the precise shape of a region andare not intended to limit the scope of the claims.

FIG. 1 is a block diagram illustrating an image processor according toexemplary embodiments.

Referring to FIG. 1, an image processor 100 may include a signalreceiver 110, a meta data analyzer 120, a tone mapper 130 and an imagecontroller 140.

The signal receiver 110 may receive image contents IC including imagedata ID and meta data IM for the image data ID. The signal receiver 110may distinguish between the image data ID and the meta data IM byanalyzing the image contents IC, may transfer the image data ID to thetone mapper 130, and may transfer the meta data IM to the meta dataanalyzer 120.

The meta data analyzer 120 may receive the meta data IM included in theimage contents IC from the signal receiver 110. In an exemplaryembodiment, the meta data IM of the image contents IC may includemaximum luminance information or the like of the image data ID for tonemapping, for example. The meta data analyzer 120 may further receivemeta data DM of a display device 200 from the display device 200. In anexemplary embodiment, the meta data DM of the display device 200 mayinclude maximum luminance information or the like of the display device200 for the tone mapping, for example. The meta data analyzer 120 mayprovide the tone mapper 130 with the meta data IM of the image contentsIC and/or the meta data DM of the display device 200.

The tone mapper 130 may convert the image data ID into output data ODbased on the meta data IM and DM received from the meta data analyzer120 such that a dynamic range of the image data ID (or the imagecontents IC) is changed corresponding to a dynamic range of the displaydevice 200.

In an exemplary embodiment, the tone mapper 130 may determine an edge ofan image represented by the image data ID, for example. In someexemplary embodiments, the tone mapper 130 may convert a data format ofthe image data ID from an RGB format to a conversion image format (e.g.,an YCbCr format) where luminance data and chrominance data areseparated, and may determine the edge by applying a high-pass filter tothe luminance data.

With respect to first image data representing a first portion of theimage not including the edge, the tone mapper 130 may perform a firsttone mapping operation (or a normal tone mapping operation) on the firstimage data included in the image data. Further, with respect to secondimage data representing a second portion of the image including theedge, the tone mapper 130 may determine whether a gray level of thesecond image data included in the image data is within a predeterminedgray range, may perform a second tone mapping operation (or a relaxedtone mapping operation) on the second image data when the gray level ofthe second image data is within the gray range (e.g., in case of a highgray edge or a low gray edge), and may perform the first tone mappingoperation on the second image data when the gray level of the secondimage data is not within the gray range. Here, the second tone mappingoperation may relatively close to linear mapping compared with the firsttone mapping operation. Thus, compared with an image generated by thefirst tone mapping operation, an image generated by the second tonemapping operation may have relatively low contrast, but may haverelatively high detail.

In some exemplary embodiments, the tone mapper 130 may obtain the numberof pixels included in the edge based on the image data ID, and mayperform a bypass operation on the entire image data ID when the numberof pixels is greater than a first threshold value. Here, the bypassoperation may linearly map the image data ID to the output data OD. Thatis, the output data OD generated by the bypass operation may increase inlinear proportion to an increase of a gray level of the image data ID.As described above, the tone mapper 130 may perform appropriate tonemapping operations according to characteristics or conditions (e.g., agray range of the edge, the number of pixels of the edge, etc.) of imagedata.

The image controller 140 may perform a post-processing operation basedon the output data OD and the meta data IM and DM. In an exemplaryembodiment, the image controller 140 may control respective luminancesof a plurality of regions that are divided according to luminance basedon the meta data IM and DM, for example. Further, the image controller140 may perform, as the post-processing operation, various imageprocessing techniques, such as contrast enhancement that maximize adifference between a bright portion and a dark portion of an image,histogram equalization that adjusts image intensities to enhancecontrast, image sharpening that increases an apparent sharpness of animage, image smoothing that removes noise in an image, etc. The imagecontroller 140 may provide the post-processed output data AD to thedisplay device 200 to display an image processed by the image processor100.

As described above, the image processor 100 may apply the second tonemapping operation (or the relaxed tone mapping operation) on the highgray edge or the low gray edge, or may apply the bypass operation whenthe number of pixels included in the edge is greater than the thresholdvalue. Accordingly, the image processor 100 may improve an accuracy ofhigh dynamic range (“HDR”) image processing while providing detailedrepresentation of the edge.

Although FIG. 1 illustrates an example of the image processor 100including the signal receiver 110, the meta data analyzer 120, the tonemapper 130 and the image controller 140, the invention is not limitedthereto, and the image processor 100 according to other exemplaryembodiments may have various configurations that perform the tonemapping operations.

Further, although FIG. 1 illustrates an example where the imageprocessor 100 is located outside the display device 200, the inventionis not limited thereto, and the image processor 100 may be located atvarious positions in other exemplary embodiments. In an exemplaryembodiment, the image processor 100 may be located inside the displaydevice 200 (e.g., inside a timing controller of the display device 200),for example.

FIG. 2 is a flowchart illustrating an image processing method accordingto exemplary embodiments, and FIGS. 3A through 3C are diagrams fordescribing an operation that determines a low gray edge or a high grayedge in an image processing method of FIG. 2.

Referring to FIGS. 2, 3A, 3B and 3C, an image processing method maydetect an edge of an image, and may apply relaxed tone mapping (orperform a second tone mapping operation) to a high gray edge and/or alow gray edge among the detected edge, thereby preventing a detail lossof an edge portion in a high gray region and/or a low gray region.

An image processor may receive image contents including image data andmeta data for the image data (S110). To detect an edge of an imagerepresented by the image data, a data format of the image data may beconverted from an RGB format into a conversion image format whereluminance data and chrominance data are separated (S120). In anexemplary embodiment, the conversion image format may be an YCoCg formator an YCbCr format, for example.

The edge of the image represented by the image data may be determinedbased on the luminance data (S130). In an exemplary embodiment, the edgeof the image may be determined by applying a high-pass filter to theluminance data, for example. In some exemplary embodiments, asillustrated in FIGS. 3A and 3B, the edge of a first image I1 representedby the image data may be determined based on the luminance data, and asecond image I2 may be an image including only the edge detected basedon the luminance data.

With respect to first image data representing a first portion of theimage I1 not including the edge of the image (S130: NO), a first tonemapping operation may be performed on the first image data included inthe image data (S160). In an exemplary embodiment, since the firstportion not including the edge may not require high detail, the firsttone mapping operation may be performed to enhance contrast, forexample.

With respect to second image data representing a second portion of theimage I1 including the edge of the image (S130: YES), it may bedetermined whether a gray level of the second image data included in theimage data is within a predetermined gray range (S140). In someexemplary embodiments, the gray range may include at least one of afirst gray range (e.g., a low gray range) less than a first thresholdgray level (e.g., 64-gray level) and a second gray range (e.g., a highgray range) greater than a second threshold gray level (e.g., 220-graylevel), and the second threshold gray level may be greater than thefirst threshold gray level, for example. In an exemplary embodiment, thegray range may include the first gray range (i.e., the low gray range)ranging from 0-gray level to 64-gray level and the second gray range(i.e., the high gray range) ranging from 220-gray level to 255-graylevel, for example. In some exemplary embodiments, at least one of thefirst gray range and the second gray range may be adjusted based on anaverage gray level of the image data. In an exemplary embodiment, in acase where the average gray level of the image data is relatively low,the first threshold gray level and/or the second threshold gray levelmay be lowered, for example.

As illustrated in FIG. 3B and 3C, a third image I3 may be an imageincluding only a high gray edge that is an edge within the high grayrange among the edge of the second image I2 and a low gray edge that isan edge within the low gray range among the edge of the second image I2.

If the gray level of the second image data is within the gray range(S140: YES), a second tone mapping operation may be performed on thesecond image data (S150). In an exemplary embodiment, when the graylevel of the second image data is within the low gray range (e.g., from0-gray level to 64-gray level) or within the high gray range (from220-gray level to 255-gray level), the second tone mapping operation maybe performed to provide the high detail of the low gray edge and thehigh gray edge, for example.

Alternatively, when the gray level of the second image data is notwithin the gray range (S140: NO), the first tone mapping operation maybe performed on the second image data (S160). In an exemplaryembodiment, when the second data are not within the low gray range orthe high gray range, for example, the high detail may not be desired,and thus the first tone mapping operation may be performed to enhancethe contrast.

FIG. 4A is a graph for describing a first tone mapping operation in animage processing method of FIG. 2, FIG. 4B is a graph for describing asecond tone mapping operation in an image processing method of FIG. 2,FIG. 5A is a graph for describing output data by a first tone mappingoperation in an image processing method of FIG. 2, FIG. 5B is a graphfor describing output data by a second tone mapping operation in animage processing method of FIG. 2, FIG. 6A is a diagram illustrating anexample of an image generated by a first tone mapping operation in animage processing method of FIG. 2, and FIG. 6B is a diagram illustratingan example of an image generated by a second tone mapping operation inan image processing method of FIG. 2.

Referring to FIGS. 4A, 4B, 5A, 5B, 6A and 6B, an image processing methodmay select an appropriate tone mapping operation according tocharacteristics or conditions (e.g., a gray range, a color, etc. of anedge) of image data.

As illustrated in FIG. 4A, a first tone mapping operation may convertimage data (or input data) ID into output data OD using a firstconversion function. In some exemplary embodiments, the image data IDand the output data OD may have the same number of bits. In an exemplaryembodiment, each of the image data ID and the output data OD may have 8bits to represent 256 gray levels, for example. In other exemplaryembodiments, the image data ID and the output data OD may have differentnumbers of bits. In an exemplary embodiment, the image data ID have 8bits to represent 256 gray levels, and the output data OD may have 12bits to represent 4,096 gray levels, for example.

As illustrated in FIG. 5A, compared with a bypass operation, the firsttone mapping operation may convert the image data ID into the outputdata OD such that gray levels of the image data ID in a low gray regionmay become further lower and gray levels of the image data ID in a highgray region may become further higher.

As illustrated in FIG. 4B, a second tone mapping operation may convertthe image data ID into the output data OD using a second conversionfunction. The second tone mapping operation may be an intermediateoperation between the first tone mapping operation and the bypassoperation.

As illustrated in FIG. 5B, compared with the first tone mappingoperation, an amount of change from the image data ID to the output dataOD may be relatively small. In some exemplary embodiments, in a firstgray range (e.g., a low gray range), the output data OD generated by thefirst tone mapping operation may be less than or equal to the outputdata OD generated by the second tone mapping operation. Further, in asecond gray range (e.g., in a high gray range), the output datagenerated by the first tone mapping operation may be greater than orequal to the output data generated by the second tone mapping operation.

In some exemplary embodiments, in a case where the image data ID and theoutput data OD have the same number of bits, a first absolute differencebetween the image data ID and the output data OD generated by the firsttone mapping operation may be greater than or equal to a second absolutedifference between the image data ID and the output data OD generated bythe second tone mapping operation. Further, a third absolute differencebetween the output data OD generated by the first tone mapping operationand the output data OD generated by the bypass operation may be greaterthan or equal to a fourth absolute difference between the output data ODgenerated by the second tone mapping operation and the output data ODgenerated by the bypass operation.

Accordingly, as illustrated in FIGS. 6A and 6B, the first tone mappingoperation may enhance the contrast compared with the second tone mappingoperation. Thus, a fourth image I4 generated by the first tone mappingoperation have a relatively high contrast compared with a fifth image I5generated by the second tone mapping operation. However, the fifth imageI5 generated by the second tone mapping operation may provide highdetail of a low gray edge and a high gray edge compared with the fourthimage I4 generated by the first tone mapping operation. In an exemplaryembodiment, although windows of a building in a region A of the fourthimage I4 are not clearly identified, the windows of the building in theregion A′ of the fifth image I5 may be clearly identified, for example.

FIG. 7 is a flowchart illustrating an image processing method accordingto exemplary embodiments, FIG. 8A is a diagram illustrating an exampleof an image generated by a first tone mapping operation in an imageprocessing method of FIG. 7, and FIG. 8B is a diagram illustrating anexample of an image generated by a second tone mapping operation in animage processing method of FIG. 7.

Referring to FIGS. 7, 8A and 8B, an image processing method may detectan edge of an image, and, when the number of pixels of the detected edgeis greater than a first threshold value, may apply linear tone mapping(i.e., perform a bypass operation) to the entire image data in acorresponding frame. Accordingly, an image including relatively manyedges may have high detail of the edges.

In the image processing method, image contents including image data andmeta data for the image data may be received (S210). To detect an edgeof an image represented by the image data, a data format of the imagedata may be converted from an RGB format into a conversion image formatwhere luminance data and chrominance data are separated (S220).

The number of pixels included in the edge may be obtained based on theimage data (S230). In an exemplary embodiment, the edge of the image maybe determined by applying a high-pass filter to the luminance data, andthe number of pixels included in the edge may be obtained by countingthe number of pixel data corresponding to the edge among the pixel dataincluded in the image data, for example.

It may be determined whether the number of pixels is greater than afirst threshold value (S240). When the number of pixels is greater thanthe first threshold value (S240: YES), a bypass operation may beperformed on the entire image data (S250). In an exemplary embodiment,when the image of one frame represented by the image data includes manyedges, it may be desired to provide high detail of the edges, forexample. Thus, in this case, tone mapping may not be applied, or thebypass operation that linearly maps the image data to output data may beperformed. In an exemplary embodiment, the first threshold value maycorresponding to about 18% of the number of all pixels, and, when thenumber of pixels included in the edge is about 20% of the number of allpixels, the image data may be linearly mapped to the output data, forexample.

Alternatively, when number of pixels is less than or equal to the firstthreshold value (S240: NO), a first tone mapping operation may beperformed on the entire image data (S260). In an exemplary embodiment,when the image represented by the image data does not include excessiveedges, the first tone mapping operation may be performed to enhancecontrast, for example. In an exemplary embodiment, the first thresholdvalue may corresponding to about 18% of the number of all pixels, and,when the number of pixels included in the edge is about 10% of thenumber of all pixels, the first tone mapping operation may be performedon the image data, for example.

As illustrated in FIGS. 8A and 8B, a seventh image I7 generated by thebypass operation may provide the high detail of the edges compared witha sixth image I6 generated by the first tone mapping operation. In anexemplary embodiment, although windows of a building in a region B ofthe sixth image I6 are not clearly identified, the windows of thebuilding in the region B′ of the seventh image I7 may be clearlyidentified, for example.

FIG. 9 is a flowchart illustrating an image processing method accordingto exemplary embodiments, and FIG. 10 is a graph for describing anoperation that sets different weights according to colors of image dataan image processing method of FIG. 9.

Referring to FIGS. 9 and 10, an image processing method may detect anedge of an image, and may apply relaxed tone mapping (or perform asecond tone mapping operation) to a high gray edge and/or a low grayedge among the detected edge. The image processing method illustrated inFIG. 9 may be similar to an image processing method illustrated in FIG.2, except that the image processing method illustrated in FIG. 9 mayapply different weights to the relaxed tone mapping (or the second tonemapping operation) depending on colors. Thus, duplicated descriptionsmay be omitted.

In the image processing method, image contents including image data andmeta data for the image data may be received (S310). To detect an edgeof an image represented by the image data, a data format of the imagedata may be converted from an RGB format into a conversion image formatwhere luminance data and chrominance data are separated (S320).

The edge of the image represented by the image data may be determinedbased on the luminance data (S330).

With respect to first image data representing a first portion of theimage not including the edge of the image (S330: NO), a first tonemapping operation may be performed on the first image data included inthe image data (S370).

With respect to second image data representing a second portion of theimage including the edge of the image (S330: YES), it may be determinedwhether a gray level of the second image data included in the image datais within a predetermined gray range (S340).

If the gray level of the second image data is within the gray range(S340: YES), a color of the second image data may be determined (S350),and a second tone mapping operation may be performed by differentweights according to the color of the second image data (S362, S364 andS366). In some exemplary embodiments, the second tone mapping operationmay convert the image data corresponding to a first color into outputdata by a second conversion function to which a first weight is applied,and may convert the image data corresponding to a second color differentfrom the first color into the output data by the second conversionfunction to which a second weight different from the first weight isapplied. In an exemplary embodiment, when the second image data are reddata (S350: RED), the second tone mapping operation may be performed byapplying a first weight to a second conversion function (S362). When thesecond image data are green data (S350: GREEN), the second tone mappingoperation may be performed by applying a second weight to the secondconversion function (S364). When the second image data are blue data(S350: BLUE), the second tone mapping operation may be performed byapplying a third weight to the second conversion function (S366).

In an exemplary embodiment, as illustrated in FIG. 10, since differentcolors may have different amounts of relationship with detailedrepresentation of the edge, the tone mapping may be performed with thedifferent weights for the respective red, green and blue data, forexample. Accordingly, an accuracy of HDR image processing may beimproved while providing detailed representation of the edge.

FIG. 11 is a flowchart illustrating an image processing method accordingto exemplary embodiments.

Referring to FIG. 11, an image processing method may detect an edge ofan image, and may perform various tone mapping operations based on agray range of the edge and the number of pixels included in the edge.However, since the image processing method may be similar to imageprocessing methods of FIGS. 2 and 7, duplicated descriptions may beomitted.

In the image processing method, image contents including image data andmeta data for the image data may be received (S410). To detect an edgeof an image represented by the image data, a data format of the imagedata may be converted from an RGB format into a conversion image formatwhere luminance data and chrominance data are separated (S420).

The number of pixels included in the edge may be obtained based on theimage data (S430).

It may be determined whether the number of pixels is greater than afirst threshold value (S440). When the number of pixels is greater thanthe first threshold value (S440: YES), a bypass operation may beperformed on the entire image data (S450).

Alternatively, when number of pixels is less than or equal to the firstthreshold value (S440: NO), it may be determined whether at least aportion of the image data includes the edge of the image (S460).

With respect to first image data representing a first portion of theimage not including the edge of the image (S460: NO), a first tonemapping operation may be performed on the first image data included inthe image data (S490).

With respect to second image data representing a second portion of theimage including the edge of the image (S460: YES), it may be determinedwhether a gray level of the second image data included in the image datais within a predetermined gray range (S470).

If the gray level of the second image data is within the gray range(S470: YES), a second tone mapping operation may be performed on thesecond image data (S480).

Alternatively, when the gray level of the second image data is notwithin the gray range (S470: NO), the first tone mapping operation maybe performed on the second image data (S490).

Although some exemplary embodiments that select a tone mapping operation(or a tone mapping conversion function) based on an edge characteristicand conditions (e.g., a gray range of an edge, the number of pixelsincluded in an edge, a color of an edge, etc.) are described above, thetone mapping operation may be selected based on various combinations ofthe edge characteristic of the image data and the conditions (e.g., agray range of an edge, the number of pixels included in an edge, a colorof an edge, etc.).

The inventions may be applied to any electronic device including animage processor. In an exemplary embodiment, the inventions may beapplied to various devices such as a television (“TV”), a digital TV, athree-dimensional (“3D”) TV, a smart phone, a mobile phone, a tabletcomputer, a personal computer (“PC”), a home appliance, a laptopcomputer, a personal digital assistant (“PDA”), a portable multimediaplayer (“PMP”), a digital camera, a music player, a portable gameconsole, a navigation device, etc.

The foregoing is illustrative of exemplary embodiments and is not to beconstrued as limiting thereof. Although a few exemplary embodiments havebeen described, those skilled in the art will readily appreciate thatmany modifications are possible in the exemplary embodiments withoutmaterially departing from the novel teachings and advantages of theinvention. Accordingly, all such modifications are intended to beincluded within the scope of the invention as defined in the claims.Therefore, it is to be understood that the foregoing is illustrative ofvarious exemplary embodiments and is not to be construed as limited tothe specific exemplary embodiments disclosed, and that modifications tothe disclosed exemplary embodiments, as well as other exemplaryembodiments, are intended to be included within the scope of theappended claims.

What is claimed is:
 1. An image processing method which converts imagedata into output data by performing tone mapping, the image processingmethod comprising: determining an edge of an image represented by theimage data; performing a first tone mapping operation on first imagedata included in the image data, the first image data representing afirst portion of the image not including the edge; determining whether agray level of second image data included in the image data is within apredetermined gray range, the second image data representing a secondportion of the image including the edge; performing a second tonemapping operation on the second image data when the gray level of thesecond image data is within the predetermined gray range; and performingthe first tone mapping operation on the second image data when the graylevel of the second image data is not within the predetermined grayrange.
 2. The image processing method of claim 1, wherein the first tonemapping operation converts the image data into the output data using afirst conversion function, and wherein the second tone mapping operationconverts the image data into the output data using a second conversionfunction different from the first conversion function.
 3. The imageprocessing method of claim 2, wherein the predetermined gray rangeincludes at least one of a first gray range less than a first thresholdgray level and a second gray range greater than a second threshold graylevel, and wherein the second threshold gray level is greater than thefirst threshold gray level.
 4. The image processing method of claim 3,wherein, in the first gray range, the output data generated by the firsttone mapping operation are less than or equal to the output datagenerated by the second tone mapping operation.
 5. The image processingmethod of claim 3, wherein, in the second gray range, the output datagenerated by the first tone mapping operation are greater than or equalto the output data generated by the second tone mapping operation. 6.The image processing method of claim 3, wherein at least one of thefirst gray range and the second gray range is adjusted based on anaverage gray level of the image data.
 7. The image processing method ofclaim 2, wherein a first absolute difference between the image data andthe output data generated by the first tone mapping operation is greaterthan or equal to a second absolute difference between the image data andthe output data generated by the second tone mapping operation.
 8. Theimage processing method of claim 1, wherein the determining the edge ofthe image includes: converting a data format of the image data from anRGB format to a conversion image format where luminance data andchrominance data are separated; and determining the edge by applying ahigh-pass filter to the luminance data.
 9. The image processing methodof claim 1, further comprising: obtaining a number of pixels included inthe edge; and performing a bypass operation on an entirety of the imagedata when the number of pixels is greater than a first threshold value.10. The image processing method of claim 9, wherein the output datagenerated by the bypass operation increase in linear proportion to anincrease of a gray level of the image data.
 11. The image processingmethod of claim 1, wherein the second tone mapping operation convertsthe image data corresponding to a first color into the output data by asecond conversion function to which a first weight is applied, andconverts the image data corresponding to a second color different fromthe first color into the output data by the second conversion functionto which a second weight different from the first weight is applied. 12.An image processor which converts image data into output data byperforming tone mapping, the image processor comprising: a signalreceiver which receives image contents including the image data and metadata for the image data; a tone mapper which determines an edge of animage represented by the image data, performs a first tone mappingoperation on first image data included in the image data, where thefirst image data represent a first portion of the image not includingthe edge, determines whether a gray level of second image data includedin the image data is within a predetermined gray range, where the secondimage data represent a second portion of the image including the edge,performs a second tone mapping operation on the second image data whenthe gray level of the second image data is within the predetermined grayrange, and performs the first tone mapping operation on the second imagedata when the gray level of the second image data is not within thepredetermined gray range; and an image controller which performs apost-processing operation on the image based on the output data and themeta data.
 13. The image processor of claim 12, wherein the first tonemapping operation converts the image data into the output data using afirst conversion function, and wherein the second tone mapping operationconverts the image data into the output data using a second conversionfunction different from the first conversion function.
 14. The imageprocessor of claim 13, wherein the predetermined gray range includes atleast one of a first gray range less than a first threshold gray leveland a second gray range greater than a second threshold gray level, andwherein the second threshold gray level is greater than the firstthreshold gray level.
 15. The image processor of claim 14, wherein, inthe first gray range, the output data generated by the first tonemapping operation are less than or equal to the output data generated bythe second tone mapping operation.
 16. The image processor of claim 14,wherein, in the second gray range, the output data generated by thefirst tone mapping operation are greater than or equal to the outputdata generated by the second tone mapping operation.
 17. The imageprocessor of claim 12, wherein the tone mapper obtains a number ofpixels included in the edge, and performs a bypass operation on anentirety of the image data when the number of pixels is greater than afirst threshold value.
 18. The image processor of claim 12, wherein thesecond tone mapping operation converts the image data corresponding to afirst color into the output data by a second conversion function towhich a first weight is applied, and converts the image datacorresponding to a second color different from the first color into theoutput data by the second conversion function to which a second weightdifferent from the first weight is applied.